Test for Linearity in Non-Parametric Regression Models
DOI:
https://doi.org/10.17713/ajs.v51i1.1047Abstract
The problem of checking the linearity of a regression relationship is addressed. The test uses nonparametric estimation techniques. The null hypothesis is that the regression function is linear; it is tested against the non-specic alternatives hypotheses. This test is based on a Hermite transform characterization of conditional expectations. A statistical test is derived, the distribution of this statistic
under the null hypothesis of linearity is determined. A power study using simulation shows the new statistic to be more sensitive to non-linearity.
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Copyright (c) 2022 Khedidja Djaballah-Djeddour, Moussa Tazerouti
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